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- W2019925130 abstract "In this paper, a few approaches to detect, localize, and investigate thefeasibility of classifying various types of power quality disturbancesare presented. The approaches are based on wavelet transformanalysis, particularly the Paul, Gaussian, and Daubechies wavelettransform. The key idea underlying the approaches are to decomposea given disturbance signal into other signals which representstransforming a one-dimensional time series into two-dimensionaltime–frequency space. The decomposition is performed using thePaul, Gaussian, and Daubechies wavelet transform techniques. Thetechniques to detect and localize disturbances with actual powerline disturbances are proposed, and then demonstrated and tested.In order to enhance the detection outcomes, the squared wavelettransform coefficients of the analyzed power line signal are utilized.Based on the results of the detection and localization, an initialinvestigation of the ability to uniquely characterize various types ofpower quality disturbances is carried out. This investigation is basedon characterizing the uniqueness of the squared wavelet transformcoefficients for each power quality disturbance." @default.
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- W2019925130 date "2008-01-01" @default.
- W2019925130 modified "2023-09-27" @default.
- W2019925130 title "POWER QUALITY DISTURBANCE MAGNITUDE CHARACTERIZATION USING WAVELET TRANSFORMATION ANALYSIS PART 1 – THEORY" @default.
- W2019925130 cites W2159860553 @default.
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- W2019925130 doi "https://doi.org/10.2316/journal.203.2008.2.203-3981" @default.
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